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I regularly come across long articles, reports, papers, ebooks, and other documents that I want to understand but realistically don’t have time to read closely. Instead of letting them pile up in a reading queue, I change the format and turn them into audio I can consume during time that would otherwise be less productive. Step-by-step: 1. I choose a long article, report, paper, ebook, or other document that I want to understand but don’t have time to read closely. 2. I upload it to Google Notebook (formerly NotebookLM) and add it as a source so NotebookLM can work directly from the material. 3. I generate an Audio Overview. NotebookLM turns the source into a conversational, podcast-style discussion that summarizes and explains the major ideas. 4. I listen while walking, driving, working out, doing chores, or running errands. 5. I follow up on what matters. After listening, I know the main ideas, what I want to investigate further, whether the document is worth reading in full, and which sections deserve closer attention. The result is essentially a personal podcast generated from whatever I need to learn. What I like about this workflow is that it doesn’t require me to find more time. It lets me use time I already have differently. Because the material is turned into a conversational discussion rather than simply being read aloud, I find it easier to stay engaged with dense material. I don’t treat the podcast as a replacement for reading the source when the details really matter. I use it as a comprehension and triage layer. Even when I eventually go back and read the original, I’m starting with a mental model of what’s in it rather than approaching it cold. The broader lesson is that AI doesn’t always need to save time by doing the work for you. Sometimes it can save time simply by changing the form of the work so it fits into your life.

I spend way too much time staring at screens, so I try to consume my content by listening while I'm out walking (usually podcasts). Lately, I've been digging into more long-form stuff from X articles and old blogs, and ElevenLabs' free app, ElevenReader, turns any wall of text into a mini audiobook using AI-generated voices. It's super simple, but genuinely really useful. Step-by-step: 1. I chose a long-form X article or older blog post that I wanted to consume away from a screen. 2. I added the text to ElevenReader. 3. I selected an AI-generated voice that was comfortable to listen to. 4. I let the app convert the article into a mini audiobook. 5. I listened while walking and kept the workflow as a simple alternative to reading everything on a screen.

YouTube is one of the best free education platforms out there, but the problem is that it takes a ton of time to sit through long videos just to find the few ideas that actually matter. That's where Gemini has been really useful for me. Since it's built into Google, I can use it to quickly summarize a specific YouTube video, or even scan the last 5–10 videos from a creator to pull out the key takeaways. Instead of spending hours watching everything, I can quickly understand the main ideas, find the best nuggets, and decide what's worth digging into deeper. It's basically a shortcut for learning from long-form content without consuming every minute of it. Step-by-step: 1. I gave Gemini the URL of a specific YouTube video when I wanted a fast summary of one piece of content. 2. For a broader view, I asked it to scan the latest five to ten videos from the same creator. 3. I had it extract the main ideas and strongest takeaways from each video. 4. I compared the summaries to find recurring themes and the most useful nuggets. 5. I used that overview to decide which videos were worth watching in full.

I ask Claude every month or so to be my Claude Code learning coach by simply typing the /insights command. It provides a hyper-personalized website report card with advice to help me use Claude Code better, with exact examples of where things go wrong, features, and prompts I should try. Step-by-step: 1. I ran the /insights command in Claude Code to analyze how I had been using the tool. 2. I reviewed the personalized website report card it generated, especially the examples of where my workflow was breaking down. 3. I pulled out the recommended features, prompts, and habits that were most relevant to the mistakes I was making. 4. I practiced those recommendations in my normal projects instead of treating the report as generic advice. 5. I repeat the exercise every month or so to see what changed and what I should learn next.

I've been taking topics I want to learn about (mostly coding docs for new technologies) and giving them to NotebookLM to create customized podcasts for my runs when there aren't interesting podcasts available from the channels I frequent. And it really is actually good and enjoyable, and not just AI slop. Step-by-step: 1. I chose a technical topic I wanted to learn and gathered the most useful documentation for it. 2. I added those sources to NotebookLM instead of relying on a generic podcast. 3. I asked NotebookLM to create a customized audio overview from the material. 4. I listened to the generated episode while running. 5. I repeated the workflow whenever I wanted an engaging podcast for a topic that existing shows had not covered.

Opposite of high school science class, I love that I never have to worry about being embarrassed to ask Claude when I don't understand something. The icing on the cake is to have it use the new chat visualizations feature. After watching (the wonderful) Hail Mary Project Movie with my kids, I needed some help trying to explain the science of Time Dilation. It helped me get a little closer. Step-by-step: 1. I told Claude the science concept I was struggling to explain: time dilation. 2. I asked it to walk through the idea in a patient, step-by-step way without making me feel rushed or embarrassed. 3. I turned on chat visualizations so the explanation included something concrete to look at. 4. I asked follow-up questions until I understood the relationship well enough to discuss it. 5. I adapted that explanation into language I could use with my children after the movie.

When my sixth-grade daughter needs math help, I sometimes feel a bit lost myself. Some of the teaching methods have changed since I was a kid, and I don't always have time to dig through her textbooks. So I use ChatGPT to walk me through problems step by step — in French, since that's how she learns — so I can actually explain them to her in a way that makes sense. Step-by-step: 1. I brought ChatGPT the sixth-grade math problem and the teaching method being used in class. 2. I asked it to solve the problem step by step instead of jumping directly to the answer. 3. I requested the explanation in French, since that is the language my daughter uses at school. 4. I asked follow-up questions about any step I did not understand myself. 5. I used the final explanation to teach the method back in a way that matched her classroom.

Over the past year, I've relied heavily on LLMs to support my French citizenship application— including drafting required letters and tracking paperwork. Although I'm already fluent, I used ChatGPT to prep for the required language exam to get familiar with the test format for 100% confidence. Step-by-step: 1. I listed the letters, forms, and paperwork required for the French citizenship application. 2. I used ChatGPT to draft the required letters and improve the wording. 3. I created a process for tracking what had been completed and what was still outstanding. 4. I asked ChatGPT to reproduce the format and expectations of the required language exam. 5. I practiced against that format until I felt fully confident despite already being fluent.